GitLab

* Per-folder tests reorganization
Co-authored-by: sgugger <sylvain.gugger@gmail.com>
Co-authored-by: Stas Bekman <stas@stason.org>

* Start the work for TFCLIPModel

* Convert to TF code (TODO: loss + doc)

* Clean up

* Fix pooled_output for TFCLIPTextTransformer - using tf.gather_nd

* assert -> raise error

* Expose TFCLIPModel

* Deal with dummy_inputs

* Add tests

* Fix all tests. TODO: manual check weight loading + add more comments

* Fix pt tf equivalence test

* fixes

* update TFCLIPVisionEmbeddings's Conv2D

* Fix loss + overwrite test_pt_tf_model_equivalence from common

* Add a comment about the change about MainLayer in test_keras_save_load

* Set return_loss=True in TFCLIPModelTester + make tests pass

* overwrite test_pt_tf_model_equivalence from tf common

* fix base_model_prefix

* Fix examples

* remove unused

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* apply review suggestions

* change self.pre_layrnorm to self.pre_layernorm

* apply more review suggestions

* return attention probs before dropout (to align with PT)

* fix weight init

* fix

* build doc

* fix missing doc

* fix for test
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Improve tests

* Install vision for tf tests

* Start the work for TFViTModel

* Convert to TF code - need to check in the follow up commits

* Clean up model code

* Expose TFViTModel

* make style

* make quality

* Add test

* make style & quality

* Fix some imports

* fix wrong usage - *kwargs => ** kwargs

* Fix Conv2D weight loading (PT->TF) issue

* Add tests for images with different sizes + fix model

* Fix some common tests for TFViTModel

* Use inputs instead of input_ids in test_compile_tf_model

* Add a comment about transpose and Conv2D in convert_tf_weight_name_to_pt_weight_name

* Avoid transpose in TFViT call

* Fix Conv2D issue in load_tf2_weights_in_pytorch_model

* Use tf.keras.layers.Conv2D instead of tf.nn.conv2d

* Using simpler heuristic to detect Conv2D layer

* Change convert_tf_weight_name_to_pt_weight_name to return TransposeType

* Check tf_weight_shape is not None before using it

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* fix missing comma

* fix input dtype
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Expose get_config() on ModelTesters

* Typo

* consistent nn. and nn.functional: p3 templates

* restore

* Squash all commits of modeling_detr_v7 branch into one

* Improve docs

* Fix tests

* Style

* Improve docs some more and fix most tests

* Fix slow tests of ViT, DeiT and DETR

* Improve replacement of batch norm

* Restructure timm backbone forward

* Make DetrForSegmentation support any timm backbone

* Fix name of output

* Address most comments by @LysandreJik

* Give better names for variables

* Conditional imports + timm in setup.py

* Address additional comments by @sgugger

* Make style, add require_timm and require_vision to testsé

* Remove train_backbone attribute of DetrConfig, add methods to freeze/unfreeze backbone

* Add png files to fixtures

* Fix type hint

* Add timm to workflows

* Add `BatchNorm2d` to the weight initialization

* Fix retain_grad test

* Replace model checkpoints by Facebook namespace

* Fix name of checkpoint in test

* Add user-friendly message when scipy is not available

* Address most comments by @patrickvonplaten

* Remove return_intermediate_layers attribute of DetrConfig and simplify Joiner

* Better initialization

* Scipy is necessary to get sklearn metrics

* Rename TimmBackbone to DetrTimmConvEncoder and rename DetrJoiner to DetrConvModel

* Make style

* Improve docs and add 2 community notebooks
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>

* First draft of deit

* More improvements

* Remove DeiTTokenizerFast from init

* Conversion script works

* Add DeiT to ViT conversion script

* Add tests, add head model, add support for deit in vit conversion script

* Update model checkpoint names

* Update image_mean and image_std, set resample to bicubic

* Improve docs

* Docs improvements

* Add DeiTForImageClassificationWithTeacher to init

* Address comments by @sgugger

* Improve feature extractors

* Make fix-copies

* Minor fixes

* Address comments by @patil-suraj

* All models uploaded

* Fix tests

* Remove labels argument from DeiTForImageClassificationWithTeacher

* Fix-copies, style and quality

* Fix tests

* Fix typo

* Multiple docs improvements

* More docs fixes

* Squash all commits into one

* Update ViTFeatureExtractor to use image_utils instead of torchvision

* Remove torchvision and add Pillow

* Small docs improvement

* Address most comments by @sgugger

* Fix tests

* Clean up conversion script

* Pooler first draft

* Fix quality

* Improve conversion script

* Make style and quality

* Make fix-copies

* Minor docs improvements

* Should use fix-copies instead of manual handling

* Revert "Should use fix-copies instead of manual handling"

This reverts commit fd4e591bce4496d41406425c82606a8fdaf8a50b.

* Place ViT in alphabetical order
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>